Bayesian Hierarchical Model for Measuring Adoption Rates in Nigerian District Hospitals Systems,

This study examines the adoption rates of new medical technologies in Nigerian district hospitals over a decade. A Bayesian hierarchical model was employed to analyse data on technology adoption across multiple districts. The model accounts for heterogeneity in hospital systems while estimating adoption proportions with uncertainty quantified through credible intervals. The analysis revealed that the rate of new medical device adoption varied significantly between hospitals, ranging from 30% to 80% among sampled facilities. Bayesian hierarchical models offer a robust framework for understanding variability in technology diffusion across healthcare systems. Further research should explore factors influencing adoption rates and the impact of these technologies on patient outcomes. Adoption Rates, Bayesian Hierarchical Models, District Hospitals, Nigeria Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.